{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# `vaex` @ PyData Budapest 2020\n",
    "\n",
    "## Machine Learning Example - Predict the duration of taxi trips\n",
    "\n",
    "To find out more details check out\n",
    "[ML impossible: Train 1 billion samples in 5 minutes on your laptop using Vaex and Scikit-Learn](https://towardsdatascience.com/ml-impossible-train-a-1-billion-sample-model-in-20-minutes-with-vaex-and-scikit-learn-on-your-9e2968e6f385).\n",
    "\n",
    "Running this notebooks requires `vaex==3.0.0`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-06-10T17:17:20.358830Z",
     "start_time": "2020-06-10T17:17:19.301832Z"
    }
   },
   "outputs": [],
   "source": [
    "import vaex\n",
    "vaex.multithreading.thread_count_default = 8\n",
    "\n",
    "import pylab as plt\n",
    "import numpy as np\n",
    "\n",
    "import warnings; warnings.simplefilter('ignore')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Initial step: reading the data and do a train/test split immediately"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-06-10T17:17:37.150683Z",
     "start_time": "2020-06-10T17:17:37.027485Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "13G\t/data/taxi/nyc_taxi_2012_zones_jovan_verify.hdf5\r\n",
      "52G\t/data/taxi/yellow_taxi_2009_2015_zones.hdf5\r\n",
      "15G\t/data/taxi/yellow_taxi_2012.hdf5\r\n",
      "12G\t/data/taxi/yellow_taxi_2012_zones.hdf5\r\n",
      "13G\t/data/taxi/yellow_taxi_2012_zones_mask.hdf5\r\n",
      "12G\t/data/taxi/yellow_taxi_2012_zones_nomask.hdf5\r\n"
     ]
    }
   ],
   "source": [
    "!du -h /data/taxi/*"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-06-10T17:17:39.094584Z",
     "start_time": "2020-06-10T17:17:38.986165Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of samples in the full dataset: 178,544,324\n",
      "Number of samples in the training set: 151,762,675\n",
      "Number of samples in the test set:       26,781,649\n"
     ]
    }
   ],
   "source": [
    "df = vaex.open('/data/taxi/yellow_taxi_2012.hdf5')\n",
    "\n",
    "# Train / test split (by date)\n",
    "df_train, df_test = df.ml.train_test_split(test_size=0.15)\n",
    "\n",
    "print(f'Number of samples in the full dataset: {len(df):,}')\n",
    "print(f'Number of samples in the training set: {len(df_train):,}')\n",
    "print(f'Number of samples in the test set:       {len(df_test):,}')\n",
    "\n",
    "# Check if the lengths of the datasets match\n",
    "assert len(df) == len(df_test) + len(df_train)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Define the label"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-06-10T17:17:59.780683Z",
     "start_time": "2020-06-10T17:17:59.777588Z"
    }
   },
   "outputs": [],
   "source": [
    "# Time in transit (minutes) - This is the target variable\n",
    "df_train['trip_duration_min'] = (df_train.dropoff_datetime - df_train.pickup_datetime) / \\\n",
    "                                   np.timedelta64(1, 'm')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Feature engineering"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-06-10T17:18:03.150521Z",
     "start_time": "2020-06-10T17:18:03.142093Z"
    }
   },
   "outputs": [],
   "source": [
    "# Speed (miles per hour) - Used for cleaning of the training data\n",
    "df_train['trip_speed_mph'] = df_train.trip_distance / \\\n",
    "                                ((df_train.dropoff_datetime - df_train.pickup_datetime) / \\\n",
    "                                np.timedelta64(1, 'h'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-06-10T17:18:08.925087Z",
     "start_time": "2020-06-10T17:18:08.712467Z"
    }
   },
   "outputs": [],
   "source": [
    "# Pickup datetime features\n",
    "df_train['pickup_time'] = df_train.pickup_datetime.dt.hour + df_train.pickup_datetime.dt.minute / 60.\n",
    "df_train['pickup_day'] = df_train.pickup_datetime.dt.dayofweek\n",
    "df_train['pickup_is_weekend'] = (df_train.pickup_day>=5).astype('int')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-06-10T17:18:18.178557Z",
     "start_time": "2020-06-10T17:18:17.740659Z"
    }
   },
   "outputs": [],
   "source": [
    "# Arc distance  in miles\n",
    "def arc_distance(theta_1, phi_1, theta_2, phi_2):\n",
    "    temp = (np.sin((theta_2-theta_1)/2*np.pi/180)**2\n",
    "           + np.cos(theta_1*np.pi/180)*np.cos(theta_2*np.pi/180) * np.sin((phi_2-phi_1)/2*np.pi/180)**2)\n",
    "    distance = 2 * np.arctan2(np.sqrt(temp), np.sqrt(1-temp))\n",
    "    return distance * 3958.8\n",
    "\n",
    "# Create the feature\n",
    "df_train['arc_distance'] = arc_distance(df_train.pickup_longitude, \n",
    "                                        df_train.pickup_latitude, \n",
    "                                        df_train.dropoff_longitude, \n",
    "                                        df_train.dropoff_latitude).jit_numba()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-06-10T17:18:20.730470Z",
     "start_time": "2020-06-10T17:18:20.694255Z"
    }
   },
   "outputs": [],
   "source": [
    "def direction_angle(theta_1, phi_1, theta_2, phi_2):\n",
    "    dtheta = theta_2 - theta_1\n",
    "    dphi = phi_2 - phi_1\n",
    "    radians = np.arctan2(dtheta, dphi)\n",
    "    return np.rad2deg(radians)\n",
    "\n",
    "# Create the feature\n",
    "df_train['direction_angle'] = direction_angle(df_train.pickup_longitude, \n",
    "                                              df_train.pickup_latitude, \n",
    "                                              df_train.dropoff_longitude, \n",
    "                                              df_train.dropoff_latitude).jit_numba()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Data cleaning"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-06-10T17:18:28.262773Z",
     "start_time": "2020-06-10T17:18:28.076107Z"
    }
   },
   "outputs": [],
   "source": [
    "# Filter abnormal number of passengers\n",
    "df_train = df_train[(df_train.passenger_count>0) & (df_train.passenger_count<7)]\n",
    "\n",
    "# Select taxi trips have travelled maximum 7 miles (but also with non-zero distance).\n",
    "df_train = df_train[(df_train.trip_distance > 0) & (df_train.trip_distance < 7)]\n",
    "\n",
    "# Filter taxi trips that have durations longer than 25 minutes or that lasted less than 3 minutes\n",
    "df_train = df_train[(df_train.trip_duration_min > 3) & (df_train.trip_duration_min < 25)]\n",
    "\n",
    "# Filter out errouneous average trip speeds.\n",
    "df_train = df_train[(df_train.trip_speed_mph > 1) & (df_train.trip_speed_mph < 60)]\n",
    "\n",
    "# Define the NYC boundaries\n",
    "long_min = -74.05\n",
    "long_max = -73.75\n",
    "lat_min = 40.58\n",
    "lat_max = 40.90\n",
    "\n",
    "# Make a selection based on the boundaries\n",
    "df_train = df_train[(df_train.pickup_longitude > long_min)  & (df_train.pickup_longitude < long_max) & \\\n",
    "                    (df_train.pickup_latitude > lat_min)    & (df_train.pickup_latitude < lat_max) & \\\n",
    "                    (df_train.dropoff_longitude > long_min) & (df_train.dropoff_longitude < long_max) & \\\n",
    "                    (df_train.dropoff_latitude > lat_min)   & (df_train.dropoff_latitude < lat_max)]\n",
    "\n",
    "# If there are unknown (N/A) pick-up or drop-off locations, choose a representative value. \n",
    "df_train['dropoff_latitude'] = df_train.dropoff_latitude.fillna(value=40.76)\n",
    "df_train['pickup_latitude'] = df_train.pickup_latitude.fillna(value=40.76)\n",
    "\n",
    "df_train['dropoff_longitude'] = df_train.dropoff_longitude.fillna(value=-73.99)\n",
    "df_train['pickup_longitude'] = df_train.pickup_longitude.fillna(value=-73.99)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## `vaex-ml`\n",
    "\n",
    "A `vaex` package for machine learning. \n",
    "\n",
    "Implements various data transformers:\n",
    " - numerical scalers\n",
    " - categorical encoders\n",
    " - PCA transformer\n",
    " - GroupBy transformers\n",
    " - more coming soon\n",
    " \n",
    "Wrappers around other popular model libraries\n",
    " - xgboost / lightgbm / catboost\n",
    " - scikit-learn\n",
    " - tensorflow / keras (coming soon!)\n",
    " \n",
    "[We are working on better integration between scikit-learn and vaex](https://github.com/scikit-learn/scikit-learn/pull/14963).\n",
    "\n",
    "scikit-learn PR #14963"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-06-10T17:19:00.330209Z",
     "start_time": "2020-06-10T17:19:00.327746Z"
    }
   },
   "outputs": [],
   "source": [
    "import vaex.ml"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Transform features: PCA of the pick-up and drop-off locations"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-06-10T17:19:13.095761Z",
     "start_time": "2020-06-10T17:19:10.972898Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[###################################-----] 100.00% elapsed time  :     1.05s =  0.0m =  0.0h\n",
      "[####################################----] 100.00% elapsed time  :     0.38s =  0.0m =  0.0h\n",
      "[####################################----] 100.00% elapsed time  :     0.23s =  0.0m =  0.0h\n",
      "[#####################################---] 100.00% elapsed time  :     0.37s =  0.0m =  0.0h\n",
      " "
     ]
    }
   ],
   "source": [
    "# PCA of the pickup and dropoff locations - helps to \"straighten out\" the coordinates\n",
    "\n",
    "# pickup transformations\n",
    "pca_pu = vaex.ml.PCA(features=['pickup_longitude', 'pickup_latitude'], n_components=2, progress=True)\n",
    "df_train = pca_pu.fit_transform(df_train)\n",
    "\n",
    "# dropoff transformations\n",
    "pca_do = vaex.ml.PCA(features=['dropoff_longitude', 'dropoff_latitude'], n_components=2, progress=True)\n",
    "df_train = pca_do.fit_transform(df_train)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Preview the new columns (PCA transformations)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-06-10T17:19:19.141444Z",
     "start_time": "2020-06-10T17:19:17.874499Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<thead>\n",
       "<tr><th>#                                      </th><th>vendor_id  </th><th>pickup_datetime              </th><th>dropoff_datetime             </th><th>passenger_count  </th><th>payment_type  </th><th>trip_distance      </th><th>pickup_longitude  </th><th>pickup_latitude  </th><th>rate_code  </th><th>store_and_fwd_flag  </th><th>dropoff_longitude  </th><th>dropoff_latitude  </th><th>fare_amount       </th><th>surcharge  </th><th>mta_tax  </th><th>tip_amount        </th><th>tolls_amount  </th><th>total_amount      </th><th>trip_duration_min  </th><th>trip_speed_mph    </th><th>pickup_time       </th><th>pickup_day  </th><th>pickup_is_weekend  </th><th>arc_distance       </th><th>direction_angle    </th><th>PCA_0                </th><th>PCA_1                 </th><th>PCA_2                </th><th>PCA_3                 </th></tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "<tr><td><i style='opacity: 0.6'>0</i>          </td><td>VTS        </td><td>2012-02-11 23:30:00.000000000</td><td>2012-02-11 23:39:00.000000000</td><td>1                </td><td>CSH           </td><td>1.2599999904632568 </td><td>-73.97868347167969</td><td>40.7244987487793 </td><td>1.0        </td><td>nan                 </td><td>-73.99909973144531 </td><td>40.729671478271484</td><td>6.5               </td><td>0.5        </td><td>0.5      </td><td>0.0               </td><td>0.0           </td><td>7.5               </td><td>9.0                </td><td>8.399999936421713 </td><td>23.5              </td><td>5           </td><td>1                  </td><td>1.4140833616256714 </td><td>-75.78253936767578 </td><td>-0.020595001056790352</td><td>-0.017823772504925728 </td><td>-0.029927730560302734</td><td>0.004115740768611431  </td></tr>\n",
       "<tr><td><i style='opacity: 0.6'>1</i>          </td><td>VTS        </td><td>2012-02-11 23:25:00.000000000</td><td>2012-02-11 23:40:00.000000000</td><td>3                </td><td>CRD           </td><td>3.2300000190734863 </td><td>-73.94949340820312</td><td>40.71410369873047</td><td>1.0        </td><td>nan                 </td><td>-74.00199127197266 </td><td>40.71927261352539 </td><td>10.899999618530273</td><td>0.5        </td><td>0.5      </td><td>2.8499999046325684</td><td>0.0           </td><td>14.75             </td><td>15.0               </td><td>12.920000076293945</td><td>23.416666666666668</td><td>5           </td><td>1                  </td><td>3.628631830215454  </td><td>-84.3768081665039  </td><td>-0.01142774149775505 </td><td>-0.0474223867058754   </td><td>-0.04016195982694626 </td><td>0.0006867535412311554 </td></tr>\n",
       "<tr><td><i style='opacity: 0.6'>2</i>          </td><td>VTS        </td><td>2012-02-11 22:44:00.000000000</td><td>2012-02-11 22:50:00.000000000</td><td>2                </td><td>CSH           </td><td>1.840000033378601  </td><td>-73.93893432617188</td><td>40.75250244140625</td><td>1.0        </td><td>nan                 </td><td>-73.96456146240234 </td><td>40.760337829589844</td><td>6.900000095367432 </td><td>0.5        </td><td>0.5      </td><td>0.0               </td><td>0.0           </td><td>7.900000095367432 </td><td>6.0                </td><td>18.40000033378601 </td><td>22.733333333333334</td><td>5           </td><td>1                  </td><td>1.776997447013855  </td><td>-72.99921417236328 </td><td>0.02564183808863163  </td><td>-0.03286890685558319  </td><td>0.014821933582425117 </td><td>-0.007320371922105551 </td></tr>\n",
       "<tr><td><i style='opacity: 0.6'>3</i>          </td><td>VTS        </td><td>2012-02-11 23:20:00.000000000</td><td>2012-02-11 23:39:00.000000000</td><td>1                </td><td>CRD           </td><td>5.510000228881836  </td><td>-73.9596176147461 </td><td>40.80888366699219</td><td>1.0        </td><td>nan                 </td><td>-73.98733520507812 </td><td>40.74416732788086 </td><td>15.699999809265137</td><td>0.5        </td><td>0.5      </td><td>3.240000009536743 </td><td>0.0           </td><td>19.940000534057617</td><td>19.0               </td><td>17.400000722784746</td><td>23.333333333333332</td><td>5           </td><td>1                  </td><td>2.278529644012451  </td><td>-156.8148651123047 </td><td>0.058389149606227875 </td><td>0.01747247390449047   </td><td>-0.011329693719744682</td><td>0.0024888506159186363 </td></tr>\n",
       "<tr><td><i style='opacity: 0.6'>4</i>          </td><td>VTS        </td><td>2012-02-11 22:41:00.000000000</td><td>2012-02-11 22:46:00.000000000</td><td>1                </td><td>CSH           </td><td>0.7900000214576721 </td><td>-74.00645446777344</td><td>40.70814514160156</td><td>1.0        </td><td>nan                 </td><td>-73.99230194091797 </td><td>40.74345779418945 </td><td>4.900000095367432 </td><td>0.5        </td><td>0.5      </td><td>0.0               </td><td>0.0           </td><td>5.900000095367432 </td><td>5.0                </td><td>9.480000257492065 </td><td>22.683333333333334</td><td>5           </td><td>1                  </td><td>1.186814308166504  </td><td>21.83981704711914  </td><td>-0.05032758042216301 </td><td>-0.005388250574469566 </td><td>-0.014699360355734825</td><td>0.006206006743013859  </td></tr>\n",
       "<tr><td>...                                    </td><td>...        </td><td>...                          </td><td>...                          </td><td>...              </td><td>...           </td><td>...                </td><td>...               </td><td>...              </td><td>...        </td><td>...                 </td><td>...                </td><td>...               </td><td>...               </td><td>...        </td><td>...      </td><td>...               </td><td>...           </td><td>...               </td><td>...                </td><td>...               </td><td>...               </td><td>...         </td><td>...                </td><td>...                </td><td>...                </td><td>...                  </td><td>...                   </td><td>...                  </td><td>...                   </td></tr>\n",
       "<tr><td><i style='opacity: 0.6'>119,415,361</i></td><td>CMT        </td><td>2012-12-24 10:37:56.000000000</td><td>2012-12-24 10:47:08.000000000</td><td>1                </td><td>CSH           </td><td>3.799999952316284  </td><td>-73.87118530273438</td><td>40.77067947387695</td><td>1.0        </td><td>0.0                 </td><td>-73.9106216430664  </td><td>40.745765686035156</td><td>12.5              </td><td>0.0        </td><td>0.5      </td><td>0.0               </td><td>0.0           </td><td>13.0              </td><td>9.2                </td><td>24.78260838467142 </td><td>10.616666666666667</td><td>0           </td><td>0                  </td><td>2.7663631439208984 </td><td>-122.28251647949219</td><td>0.08078788220882416  </td><td>-0.07621920108795166  </td><td>0.032961733639240265 </td><td>-0.06016731262207031  </td></tr>\n",
       "<tr><td><i style='opacity: 0.6'>119,415,362</i></td><td>CMT        </td><td>2012-12-24 10:46:58.000000000</td><td>2012-12-24 10:56:29.000000000</td><td>1                </td><td>CSH           </td><td>1.7999999523162842 </td><td>-73.96009063720703</td><td>40.77359390258789</td><td>1.0        </td><td>0.0                 </td><td>-73.97677612304688 </td><td>40.750755310058594</td><td>9.0               </td><td>0.0        </td><td>0.5      </td><td>0.0               </td><td>0.0           </td><td>9.5               </td><td>9.516666666666667  </td><td>11.348511082904768</td><td>10.766666666666667</td><td>0           </td><td>0                  </td><td>1.2324864864349365 </td><td>-143.84877014160156</td><td>0.029851939529180527 </td><td>-0.003293338231742382 </td><td>4.210078623145819e-05</td><td>-0.0025686207227408886</td></tr>\n",
       "<tr><td><i style='opacity: 0.6'>119,415,363</i></td><td>CMT        </td><td>2012-12-24 07:10:44.000000000</td><td>2012-12-24 07:16:48.000000000</td><td>1                </td><td>CSH           </td><td>2.0999999046325684 </td><td>-73.99629211425781</td><td>40.73793411254883</td><td>1.0        </td><td>0.0                 </td><td>-73.97488403320312 </td><td>40.75730514526367 </td><td>8.0               </td><td>0.0        </td><td>0.5      </td><td>0.0               </td><td>0.0           </td><td>8.5               </td><td>6.066666666666666  </td><td>20.76922982603639 </td><td>7.166666666666667 </td><td>0           </td><td>0                  </td><td>1.5245623588562012 </td><td>47.85973358154297  </td><td>-0.0203888900578022  </td><td>0.004324158653616905  </td><td>0.006527906283736229 </td><td>-0.0004675083328038454</td></tr>\n",
       "<tr><td><i style='opacity: 0.6'>119,415,364</i></td><td>CMT        </td><td>2012-12-24 21:09:56.000000000</td><td>2012-12-24 21:13:22.000000000</td><td>1                </td><td>CSH           </td><td>0.30000001192092896</td><td>-73.96232604980469</td><td>40.77641296386719</td><td>1.0        </td><td>0.0                 </td><td>-73.95834350585938 </td><td>40.774906158447266</td><td>4.0               </td><td>0.5        </td><td>0.5      </td><td>0.0               </td><td>0.0           </td><td>5.0               </td><td>3.433333333333333  </td><td>5.242718654928855 </td><td>21.15             </td><td>0           </td><td>0                  </td><td>0.27666980028152466</td><td>110.72425842285156 </td><td>0.030769556760787964 </td><td>0.00018547754734754562</td><td>0.030373375862836838 </td><td>-0.004311750642955303 </td></tr>\n",
       "<tr><td><i style='opacity: 0.6'>119,415,365</i></td><td>CMT        </td><td>2012-12-24 20:07:23.000000000</td><td>2012-12-24 20:20:18.000000000</td><td>1                </td><td>CSH           </td><td>1.100000023841858  </td><td>-73.97209167480469</td><td>40.75520706176758</td><td>4.0        </td><td>0.0                 </td><td>-73.98250579833984 </td><td>40.76253890991211 </td><td>9.5               </td><td>0.5        </td><td>0.5      </td><td>0.0               </td><td>0.0           </td><td>10.5              </td><td>12.916666666666666 </td><td>5.109677530104114 </td><td>20.116666666666667</td><td>0           </td><td>0                  </td><td>0.7330145239830017 </td><td>-54.85333251953125 </td><td>0.007940372452139854 </td><td>-0.004701853729784489 </td><td>0.006594730541110039 </td><td>0.008777984417974949  </td></tr>\n",
       "</tbody>\n",
       "</table>"
      ],
      "text/plain": [
       "#            vendor_id    pickup_datetime                dropoff_datetime               passenger_count    payment_type    trip_distance        pickup_longitude    pickup_latitude    rate_code    store_and_fwd_flag    dropoff_longitude    dropoff_latitude    fare_amount         surcharge    mta_tax    tip_amount          tolls_amount    total_amount        trip_duration_min    trip_speed_mph      pickup_time         pickup_day    pickup_is_weekend    arc_distance         direction_angle      PCA_0                  PCA_1                   PCA_2                  PCA_3\n",
       "0            VTS          2012-02-11 23:30:00.000000000  2012-02-11 23:39:00.000000000  1                  CSH             1.2599999904632568   -73.97868347167969  40.7244987487793   1.0          nan                   -73.99909973144531   40.729671478271484  6.5                 0.5          0.5        0.0                 0.0             7.5                 9.0                  8.399999936421713   23.5                5             1                    1.4140833616256714   -75.78253936767578   -0.020595001056790352  -0.017823772504925728   -0.029927730560302734  0.004115740768611431\n",
       "1            VTS          2012-02-11 23:25:00.000000000  2012-02-11 23:40:00.000000000  3                  CRD             3.2300000190734863   -73.94949340820312  40.71410369873047  1.0          nan                   -74.00199127197266   40.71927261352539   10.899999618530273  0.5          0.5        2.8499999046325684  0.0             14.75               15.0                 12.920000076293945  23.416666666666668  5             1                    3.628631830215454    -84.3768081665039    -0.01142774149775505   -0.0474223867058754     -0.04016195982694626   0.0006867535412311554\n",
       "2            VTS          2012-02-11 22:44:00.000000000  2012-02-11 22:50:00.000000000  2                  CSH             1.840000033378601    -73.93893432617188  40.75250244140625  1.0          nan                   -73.96456146240234   40.760337829589844  6.900000095367432   0.5          0.5        0.0                 0.0             7.900000095367432   6.0                  18.40000033378601   22.733333333333334  5             1                    1.776997447013855    -72.99921417236328   0.02564183808863163    -0.03286890685558319    0.014821933582425117   -0.007320371922105551\n",
       "3            VTS          2012-02-11 23:20:00.000000000  2012-02-11 23:39:00.000000000  1                  CRD             5.510000228881836    -73.9596176147461   40.80888366699219  1.0          nan                   -73.98733520507812   40.74416732788086   15.699999809265137  0.5          0.5        3.240000009536743   0.0             19.940000534057617  19.0                 17.400000722784746  23.333333333333332  5             1                    2.278529644012451    -156.8148651123047   0.058389149606227875   0.01747247390449047     -0.011329693719744682  0.0024888506159186363\n",
       "4            VTS          2012-02-11 22:41:00.000000000  2012-02-11 22:46:00.000000000  1                  CSH             0.7900000214576721   -74.00645446777344  40.70814514160156  1.0          nan                   -73.99230194091797   40.74345779418945   4.900000095367432   0.5          0.5        0.0                 0.0             5.900000095367432   5.0                  9.480000257492065   22.683333333333334  5             1                    1.186814308166504    21.83981704711914    -0.05032758042216301   -0.005388250574469566   -0.014699360355734825  0.006206006743013859\n",
       "...          ...          ...                            ...                            ...                ...             ...                  ...                 ...                ...          ...                   ...                  ...                 ...                 ...          ...        ...                 ...             ...                 ...                  ...                 ...                 ...           ...                  ...                  ...                  ...                    ...                     ...                    ...\n",
       "119,415,361  CMT          2012-12-24 10:37:56.000000000  2012-12-24 10:47:08.000000000  1                  CSH             3.799999952316284    -73.87118530273438  40.77067947387695  1.0          0.0                   -73.9106216430664    40.745765686035156  12.5                0.0          0.5        0.0                 0.0             13.0                9.2                  24.78260838467142   10.616666666666667  0             0                    2.7663631439208984   -122.28251647949219  0.08078788220882416    -0.07621920108795166    0.032961733639240265   -0.06016731262207031\n",
       "119,415,362  CMT          2012-12-24 10:46:58.000000000  2012-12-24 10:56:29.000000000  1                  CSH             1.7999999523162842   -73.96009063720703  40.77359390258789  1.0          0.0                   -73.97677612304688   40.750755310058594  9.0                 0.0          0.5        0.0                 0.0             9.5                 9.516666666666667    11.348511082904768  10.766666666666667  0             0                    1.2324864864349365   -143.84877014160156  0.029851939529180527   -0.003293338231742382   4.210078623145819e-05  -0.0025686207227408886\n",
       "119,415,363  CMT          2012-12-24 07:10:44.000000000  2012-12-24 07:16:48.000000000  1                  CSH             2.0999999046325684   -73.99629211425781  40.73793411254883  1.0          0.0                   -73.97488403320312   40.75730514526367   8.0                 0.0          0.5        0.0                 0.0             8.5                 6.066666666666666    20.76922982603639   7.166666666666667   0             0                    1.5245623588562012   47.85973358154297    -0.0203888900578022    0.004324158653616905    0.006527906283736229   -0.0004675083328038454\n",
       "119,415,364  CMT          2012-12-24 21:09:56.000000000  2012-12-24 21:13:22.000000000  1                  CSH             0.30000001192092896  -73.96232604980469  40.77641296386719  1.0          0.0                   -73.95834350585938   40.774906158447266  4.0                 0.5          0.5        0.0                 0.0             5.0                 3.433333333333333    5.242718654928855   21.15               0             0                    0.27666980028152466  110.72425842285156   0.030769556760787964   0.00018547754734754562  0.030373375862836838   -0.004311750642955303\n",
       "119,415,365  CMT          2012-12-24 20:07:23.000000000  2012-12-24 20:20:18.000000000  1                  CSH             1.100000023841858    -73.97209167480469  40.75520706176758  4.0          0.0                   -73.98250579833984   40.76253890991211   9.5                 0.5          0.5        0.0                 0.0             10.5                12.916666666666666   5.109677530104114   20.116666666666667  0             0                    0.7330145239830017   -54.85333251953125   0.007940372452139854   -0.004701853729784489   0.006594730541110039   0.008777984417974949"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_train"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-06-10T17:19:34.168429Z",
     "start_time": "2020-06-10T17:19:33.041797Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1008x360 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(14, 5))\n",
    "\n",
    "plt.subplot(121)\n",
    "plt.title('pickup - original')\n",
    "df_train.plot(df_train.pickup_longitude, df_train.pickup_latitude,\n",
    "           colormap='plasma', f='log1p', shape=256, colorbar=False)\n",
    "\n",
    "plt.subplot(122)\n",
    "plt.title('pickup - PCA transformed')\n",
    "df_train.plot(df_train.PCA_0, df_train.PCA_1,\n",
    "           colormap='plasma', f='log1p', shape=256, colorbar=False)\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Handling temporal (cyclical) features\n",
    "\n",
    "- Assume the temporal feature is the θ coordinate of a unit circle in polar coordinates. Conver it to Cartesian (x,y) coordinates. This preserves the continuity (12 o'clock is close to 1 o'clock)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-06-10T17:19:47.860170Z",
     "start_time": "2020-06-10T17:19:47.845178Z"
    }
   },
   "outputs": [],
   "source": [
    "# Time\n",
    "cycl_transform_time = vaex.ml.CycleTransformer(features=['pickup_time'], n=24)\n",
    "df_train = cycl_transform_time.fit_transform(df_train)\n",
    "\n",
    "# Day\n",
    "cycl_transform_day = vaex.ml.CycleTransformer(features=['pickup_day'], n=7)\n",
    "df_train = cycl_transform_day.fit_transform(df_train)\n",
    "\n",
    "# Direction angle\n",
    "cycl_transform_angle = vaex.ml.CycleTransformer(features=['direction_angle'], n=360)\n",
    "df_train = cycl_transform_angle.fit_transform(df_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-06-10T17:19:50.581245Z",
     "start_time": "2020-06-10T17:19:48.720755Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Let's see how the transformed date would look like\n",
    "df_train.plot(x='pickup_time_x', y='pickup_time_y',\n",
    "              shape=128, limits=[-1, 1],\n",
    "              figsize=(5, 5),\n",
    "              colorbar=False)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Scaling of numerical features"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-06-10T17:20:13.174346Z",
     "start_time": "2020-06-10T17:20:11.776303Z"
    }
   },
   "outputs": [],
   "source": [
    "# Standard scaling of numerical features\n",
    "standard_scaler = vaex.ml.StandardScaler(features=['arc_distance'])\n",
    "df_train = standard_scaler.fit_transform(df_train)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Preview the training features"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-06-10T17:20:14.273170Z",
     "start_time": "2020-06-10T17:20:13.925675Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<thead>\n",
       "<tr><th>#                            </th><th style=\"text-align: right;\">      PCA_0</th><th style=\"text-align: right;\">      PCA_1</th><th style=\"text-align: right;\">      PCA_2</th><th style=\"text-align: right;\">       PCA_3</th><th style=\"text-align: right;\">  standard_scaled_arc_distance</th><th style=\"text-align: right;\">  pickup_time_x</th><th style=\"text-align: right;\">  pickup_day_x</th><th style=\"text-align: right;\">  direction_angle_x</th><th style=\"text-align: right;\">  pickup_time_y</th><th style=\"text-align: right;\">  pickup_day_y</th><th style=\"text-align: right;\">  direction_angle_y</th><th style=\"text-align: right;\">  pickup_is_weekend</th></tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "<tr><td><i style='opacity: 0.6'>0</i></td><td style=\"text-align: right;\">-0.020595  </td><td style=\"text-align: right;\">-0.0178238 </td><td style=\"text-align: right;\">-0.0299277 </td><td style=\"text-align: right;\"> 0.00411574 </td><td style=\"text-align: right;\">                     0.274201 </td><td style=\"text-align: right;\">       0.991445</td><td style=\"text-align: right;\">     -0.222521</td><td style=\"text-align: right;\">          0.245603 </td><td style=\"text-align: right;\">      -0.130526</td><td style=\"text-align: right;\">     -0.974928</td><td style=\"text-align: right;\">          -0.969371</td><td style=\"text-align: right;\">                  1</td></tr>\n",
       "<tr><td><i style='opacity: 0.6'>1</i></td><td style=\"text-align: right;\">-0.0114277 </td><td style=\"text-align: right;\">-0.0474224 </td><td style=\"text-align: right;\">-0.040162  </td><td style=\"text-align: right;\"> 0.000686754</td><td style=\"text-align: right;\">                     2.73354  </td><td style=\"text-align: right;\">       0.988362</td><td style=\"text-align: right;\">     -0.222521</td><td style=\"text-align: right;\">          0.0979857</td><td style=\"text-align: right;\">      -0.152123</td><td style=\"text-align: right;\">     -0.974928</td><td style=\"text-align: right;\">          -0.995188</td><td style=\"text-align: right;\">                  1</td></tr>\n",
       "<tr><td><i style='opacity: 0.6'>2</i></td><td style=\"text-align: right;\"> 0.0256418 </td><td style=\"text-align: right;\">-0.0328689 </td><td style=\"text-align: right;\"> 0.0148219 </td><td style=\"text-align: right;\">-0.00732037 </td><td style=\"text-align: right;\">                     0.67723  </td><td style=\"text-align: right;\">       0.945519</td><td style=\"text-align: right;\">     -0.222521</td><td style=\"text-align: right;\">          0.292385 </td><td style=\"text-align: right;\">      -0.325568</td><td style=\"text-align: right;\">     -0.974928</td><td style=\"text-align: right;\">          -0.956301</td><td style=\"text-align: right;\">                  1</td></tr>\n",
       "<tr><td><i style='opacity: 0.6'>3</i></td><td style=\"text-align: right;\"> 0.0583891 </td><td style=\"text-align: right;\"> 0.0174725 </td><td style=\"text-align: right;\">-0.0113297 </td><td style=\"text-align: right;\"> 0.00248885 </td><td style=\"text-align: right;\">                     1.2342   </td><td style=\"text-align: right;\">       0.984808</td><td style=\"text-align: right;\">     -0.222521</td><td style=\"text-align: right;\">         -0.919238 </td><td style=\"text-align: right;\">      -0.173648</td><td style=\"text-align: right;\">     -0.974928</td><td style=\"text-align: right;\">          -0.393703</td><td style=\"text-align: right;\">                  1</td></tr>\n",
       "<tr><td><i style='opacity: 0.6'>4</i></td><td style=\"text-align: right;\">-0.0503276 </td><td style=\"text-align: right;\">-0.00538825</td><td style=\"text-align: right;\">-0.0146994 </td><td style=\"text-align: right;\"> 0.00620601 </td><td style=\"text-align: right;\">                     0.0218105</td><td style=\"text-align: right;\">       0.941176</td><td style=\"text-align: right;\">     -0.222521</td><td style=\"text-align: right;\">          0.928228 </td><td style=\"text-align: right;\">      -0.337917</td><td style=\"text-align: right;\">     -0.974928</td><td style=\"text-align: right;\">           0.372013</td><td style=\"text-align: right;\">                  1</td></tr>\n",
       "<tr><td><i style='opacity: 0.6'>5</i></td><td style=\"text-align: right;\">-0.0275531 </td><td style=\"text-align: right;\"> 0.00711023</td><td style=\"text-align: right;\">-0.0278285 </td><td style=\"text-align: right;\"> 0.0161444  </td><td style=\"text-align: right;\">                    -0.896509 </td><td style=\"text-align: right;\">       0.994056</td><td style=\"text-align: right;\">     -0.222521</td><td style=\"text-align: right;\">          0.644808 </td><td style=\"text-align: right;\">      -0.108867</td><td style=\"text-align: right;\">     -0.974928</td><td style=\"text-align: right;\">          -0.764345</td><td style=\"text-align: right;\">                  1</td></tr>\n",
       "<tr><td><i style='opacity: 0.6'>6</i></td><td style=\"text-align: right;\">-0.0723734 </td><td style=\"text-align: right;\">-0.028767  </td><td style=\"text-align: right;\">-0.0750212 </td><td style=\"text-align: right;\">-0.0241434  </td><td style=\"text-align: right;\">                    -1.29619  </td><td style=\"text-align: right;\">       0.94693 </td><td style=\"text-align: right;\">     -0.222521</td><td style=\"text-align: right;\">          1        </td><td style=\"text-align: right;\">      -0.321439</td><td style=\"text-align: right;\">     -0.974928</td><td style=\"text-align: right;\">           0       </td><td style=\"text-align: right;\">                  1</td></tr>\n",
       "<tr><td><i style='opacity: 0.6'>7</i></td><td style=\"text-align: right;\"> 0.0626352 </td><td style=\"text-align: right;\">-0.00947211</td><td style=\"text-align: right;\"> 0.0404331 </td><td style=\"text-align: right;\">-0.00821181 </td><td style=\"text-align: right;\">                    -0.17695  </td><td style=\"text-align: right;\">       0.94693 </td><td style=\"text-align: right;\">     -0.222521</td><td style=\"text-align: right;\">         -0.733494 </td><td style=\"text-align: right;\">      -0.321439</td><td style=\"text-align: right;\">     -0.974928</td><td style=\"text-align: right;\">          -0.679696</td><td style=\"text-align: right;\">                  1</td></tr>\n",
       "<tr><td><i style='opacity: 0.6'>8</i></td><td style=\"text-align: right;\">-0.0259672 </td><td style=\"text-align: right;\">-0.0159551 </td><td style=\"text-align: right;\">-0.0287257 </td><td style=\"text-align: right;\">-0.00371009 </td><td style=\"text-align: right;\">                    -0.632151 </td><td style=\"text-align: right;\">       0.938191</td><td style=\"text-align: right;\">     -0.222521</td><td style=\"text-align: right;\">          0.502527 </td><td style=\"text-align: right;\">      -0.346117</td><td style=\"text-align: right;\">     -0.974928</td><td style=\"text-align: right;\">          -0.864562</td><td style=\"text-align: right;\">                  1</td></tr>\n",
       "<tr><td><i style='opacity: 0.6'>9</i></td><td style=\"text-align: right;\"> 0.00118875</td><td style=\"text-align: right;\"> 0.00155669</td><td style=\"text-align: right;\"> 0.00217677</td><td style=\"text-align: right;\">-0.00900871 </td><td style=\"text-align: right;\">                    -0.453891 </td><td style=\"text-align: right;\">       0.942641</td><td style=\"text-align: right;\">     -0.222521</td><td style=\"text-align: right;\">         -0.391236 </td><td style=\"text-align: right;\">      -0.333807</td><td style=\"text-align: right;\">     -0.974928</td><td style=\"text-align: right;\">           0.92029 </td><td style=\"text-align: right;\">                  1</td></tr>\n",
       "</tbody>\n",
       "</table>"
      ],
      "text/plain": [
       "  #        PCA_0        PCA_1        PCA_2         PCA_3    standard_scaled_arc_distance    pickup_time_x    pickup_day_x    direction_angle_x    pickup_time_y    pickup_day_y    direction_angle_y    pickup_is_weekend\n",
       "  0  -0.020595    -0.0178238   -0.0299277    0.00411574                        0.274201          0.991445       -0.222521            0.245603         -0.130526       -0.974928            -0.969371                    1\n",
       "  1  -0.0114277   -0.0474224   -0.040162     0.000686754                       2.73354           0.988362       -0.222521            0.0979857        -0.152123       -0.974928            -0.995188                    1\n",
       "  2   0.0256418   -0.0328689    0.0148219   -0.00732037                        0.67723           0.945519       -0.222521            0.292385         -0.325568       -0.974928            -0.956301                    1\n",
       "  3   0.0583891    0.0174725   -0.0113297    0.00248885                        1.2342            0.984808       -0.222521           -0.919238         -0.173648       -0.974928            -0.393703                    1\n",
       "  4  -0.0503276   -0.00538825  -0.0146994    0.00620601                        0.0218105         0.941176       -0.222521            0.928228         -0.337917       -0.974928             0.372013                    1\n",
       "  5  -0.0275531    0.00711023  -0.0278285    0.0161444                        -0.896509          0.994056       -0.222521            0.644808         -0.108867       -0.974928            -0.764345                    1\n",
       "  6  -0.0723734   -0.028767    -0.0750212   -0.0241434                        -1.29619           0.94693        -0.222521            1                -0.321439       -0.974928             0                           1\n",
       "  7   0.0626352   -0.00947211   0.0404331   -0.00821181                       -0.17695           0.94693        -0.222521           -0.733494         -0.321439       -0.974928            -0.679696                    1\n",
       "  8  -0.0259672   -0.0159551   -0.0287257   -0.00371009                       -0.632151          0.938191       -0.222521            0.502527         -0.346117       -0.974928            -0.864562                    1\n",
       "  9   0.00118875   0.00155669   0.00217677  -0.00900871                       -0.453891          0.942641       -0.222521           -0.391236         -0.333807       -0.974928             0.92029                     1"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Select all the features to be used for training the model\n",
    "features = df_train.get_column_names(regex='PCA*') + \\\n",
    "           df_train.get_column_names(regex='standard_scaled_*') + \\\n",
    "           df_train.get_column_names(regex='.*_x') + \\\n",
    "           df_train.get_column_names(regex='.*_y') + \\\n",
    "           ['pickup_is_weekend']\n",
    "\n",
    "# Preview the features\n",
    "df_train.head(10)[features]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Set the target variable"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-06-10T17:20:20.473613Z",
     "start_time": "2020-06-10T17:20:20.471167Z"
    }
   },
   "outputs": [],
   "source": [
    "target = 'trip_duration_min'"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Train a machine learning model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-06-10T17:20:57.695780Z",
     "start_time": "2020-06-10T17:20:24.626114Z"
    }
   },
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "6e941f6d7ef848d895b2cf673774fc96",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(FloatProgress(value=0.0, max=1.0), Label(value='In progress...')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from sklearn.linear_model import SGDRegressor\n",
    "from vaex.ml.sklearn import IncrementalPredictor\n",
    "\n",
    "# Define the base model\n",
    "model = SGDRegressor(learning_rate='constant', eta0=0.0001)\n",
    "\n",
    "# The Vaex incremental model wrapper\n",
    "vaex_model = IncrementalPredictor(features=features,\n",
    "                                  target=target,\n",
    "                                  model=model,\n",
    "                                  batch_size=11_000_000, \n",
    "                                  num_epochs=1, \n",
    "                                  shuffle=False, \n",
    "                                  prediction_name='predicted_duration_min')\n",
    "\n",
    "# Fit the model\n",
    "vaex_model.fit(df=df_train, progress='widget')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Let's see the predictions!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-06-10T17:21:09.306299Z",
     "start_time": "2020-06-10T17:21:02.133278Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([10.83679091, 17.55674479, 10.9744867 , ..., 10.45261422,\n",
       "        6.56544312,  9.10941091])"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Standard in-memory predict\n",
    "vaex_model.predict(df_train)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Vaex makes models transformers!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-06-10T17:21:17.616921Z",
     "start_time": "2020-06-10T17:21:17.267832Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<thead>\n",
       "<tr><th>#                            </th><th style=\"text-align: right;\">  trip_duration_min</th><th style=\"text-align: right;\">  predicted_duration_min</th></tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "<tr><td><i style='opacity: 0.6'>0</i></td><td style=\"text-align: right;\">                  9</td><td style=\"text-align: right;\">                 10.8368</td></tr>\n",
       "<tr><td><i style='opacity: 0.6'>1</i></td><td style=\"text-align: right;\">                 15</td><td style=\"text-align: right;\">                 17.5567</td></tr>\n",
       "<tr><td><i style='opacity: 0.6'>2</i></td><td style=\"text-align: right;\">                  6</td><td style=\"text-align: right;\">                 10.9745</td></tr>\n",
       "<tr><td><i style='opacity: 0.6'>3</i></td><td style=\"text-align: right;\">                 19</td><td style=\"text-align: right;\">                 13.2393</td></tr>\n",
       "<tr><td><i style='opacity: 0.6'>4</i></td><td style=\"text-align: right;\">                  5</td><td style=\"text-align: right;\">                 10.2093</td></tr>\n",
       "</tbody>\n",
       "</table>"
      ],
      "text/plain": [
       "  #    trip_duration_min    predicted_duration_min\n",
       "  0                    9                   10.8368\n",
       "  1                   15                   17.5567\n",
       "  2                    6                   10.9745\n",
       "  3                   19                   13.2393\n",
       "  4                    5                   10.2093"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_train = vaex_model.transform(df_train)\n",
    "# See a portion of the predictions\n",
    "df_train.head(5)['trip_duration_min', 'predicted_duration_min']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The prediction is an expression! Opprotunities for post-processing, ensembles etc..\n",
    "\n",
    "Values lower than 3 minutes are set to 3; values higher than 25 minutes are set to 25"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-06-10T17:21:27.752089Z",
     "start_time": "2020-06-10T17:21:27.748432Z"
    }
   },
   "outputs": [],
   "source": [
    "df_train['pred_final'] = df_train.predicted_duration_min.clip(3, 25)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## But.. what about the test set?!\n",
    "\n",
    "### State transfer (a.k.a the `vaex` automatic pipeline)\n",
    "\n",
    "The operations done on the data are recorded in the `state` of the DataFrame."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-06-10T17:21:42.939230Z",
     "start_time": "2020-06-10T17:21:42.931020Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'virtual_columns': {'pickup_longitude': 'fillna(__pickup_longitude, value=-73.99)',\n",
       "  'pickup_latitude': 'fillna(__pickup_latitude, value=40.76)',\n",
       "  'dropoff_longitude': 'fillna(__dropoff_longitude, value=-73.99)',\n",
       "  'dropoff_latitude': 'fillna(__dropoff_latitude, value=40.76)',\n",
       "  'trip_duration_min': '((dropoff_datetime - pickup_datetime) / var_time_delta)',\n",
       "  'trip_speed_mph': '(trip_distance / ((dropoff_datetime - pickup_datetime) / var_time_delta_1))',\n",
       "  'pickup_time': '(dt_hour(pickup_datetime) + (dt_minute(pickup_datetime) / 60.0))',\n",
       "  'pickup_day': 'dt_dayofweek(pickup_datetime)',\n",
       "  'pickup_is_weekend': \"astype((pickup_day >= 5), 'int')\",\n",
       "  'arc_distance': '_jit(__pickup_latitude, __pickup_longitude, __dropoff_latitude, __dropoff_longitude)',\n",
       "  'direction_angle': '_jit_1(__dropoff_longitude, __pickup_longitude, __dropoff_latitude, __pickup_latitude)',\n",
       "  'PCA_0': '(pickup_longitude - -73.9806109361281) * 0.5991687373455696 + (pickup_latitude - 40.75166597207298) * 0.8006227727136643',\n",
       "  'PCA_1': '(pickup_longitude - -73.9806109361281) * -0.8006227727136643 + (pickup_latitude - 40.75166597207298) * 0.5991687373455696',\n",
       "  'PCA_2': '(dropoff_longitude - -73.97893097347409) * 0.5601005594705609 + (dropoff_latitude - 40.752160151590424) * 0.8284246273987541',\n",
       "  'PCA_3': '(dropoff_longitude - -73.97893097347409) * -0.8284246273987541 + (dropoff_latitude - 40.752160151590424) * 0.5601005594705609',\n",
       "  'pickup_time_x': 'cos(((6.283185307179586 * pickup_time) / 24))',\n",
       "  'pickup_time_y': 'sin(((6.283185307179586 * pickup_time) / 24))',\n",
       "  'pickup_day_x': 'cos(((6.283185307179586 * pickup_day) / 7))',\n",
       "  'pickup_day_y': 'sin(((6.283185307179586 * pickup_day) / 7))',\n",
       "  'direction_angle_x': 'cos(((6.283185307179586 * direction_angle) / 360))',\n",
       "  'direction_angle_y': 'sin(((6.283185307179586 * direction_angle) / 360))',\n",
       "  'standard_scaled_arc_distance': '((arc_distance - 1.16717472071215) / 0.9004664861726833)',\n",
       "  'predicted_duration_min': 'incremental_prediction_function(PCA_0, PCA_1, PCA_2, PCA_3, standard_scaled_arc_distance, pickup_time_x, pickup_day_x, direction_angle_x, pickup_time_y, pickup_day_y, direction_angle_y, pickup_is_weekend)',\n",
       "  'pred_final': 'clip(predicted_duration_min, 3, 25)'},\n",
       " 'column_names': ['vendor_id',\n",
       "  'pickup_datetime',\n",
       "  'dropoff_datetime',\n",
       "  'passenger_count',\n",
       "  'payment_type',\n",
       "  'trip_distance',\n",
       "  'pickup_longitude',\n",
       "  '__pickup_longitude',\n",
       "  'pickup_latitude',\n",
       "  '__pickup_latitude',\n",
       "  'rate_code',\n",
       "  'store_and_fwd_flag',\n",
       "  'dropoff_longitude',\n",
       "  '__dropoff_longitude',\n",
       "  'dropoff_latitude',\n",
       "  '__dropoff_latitude',\n",
       "  'fare_amount',\n",
       "  'surcharge',\n",
       "  'mta_tax',\n",
       "  'tip_amount',\n",
       "  'tolls_amount',\n",
       "  'total_amount',\n",
       "  'trip_duration_min',\n",
       "  'trip_speed_mph',\n",
       "  'pickup_time',\n",
       "  'pickup_day',\n",
       "  'pickup_is_weekend',\n",
       "  'arc_distance',\n",
       "  'direction_angle',\n",
       "  'PCA_0',\n",
       "  'PCA_1',\n",
       "  'PCA_2',\n",
       "  'PCA_3',\n",
       "  'pickup_time_x',\n",
       "  'pickup_time_y',\n",
       "  'pickup_day_x',\n",
       "  'pickup_day_y',\n",
       "  'direction_angle_x',\n",
       "  'direction_angle_y',\n",
       "  'standard_scaled_arc_distance',\n",
       "  'predicted_duration_min',\n",
       "  'pred_final'],\n",
       " 'renamed_columns': [('dropoff_latitude', '__dropoff_latitude'),\n",
       "  ('pickup_latitude', '__pickup_latitude'),\n",
       "  ('dropoff_longitude', '__dropoff_longitude'),\n",
       "  ('pickup_longitude', '__pickup_longitude')],\n",
       " 'variables': {'var_time_delta': numpy.timedelta64(1,'m'),\n",
       "  'var_time_delta_1': numpy.timedelta64(1,'h')},\n",
       " 'functions': {'_jit': {'cls': 'vaex.expression.FunctionSerializableNumba',\n",
       "   'state': {'expression': '((2 * arctan2(sqrt(((sin(((((dropoff_longitude - pickup_longitude) / 2) * 3.141592653589793) / 180)) ** 2) + ((cos(((pickup_longitude * 3.141592653589793) / 180)) * cos(((dropoff_longitude * 3.141592653589793) / 180))) * (sin(((((dropoff_latitude - pickup_latitude) / 2) * 3.141592653589793) / 180)) ** 2)))), sqrt((1 - ((sin(((((dropoff_longitude - pickup_longitude) / 2) * 3.141592653589793) / 180)) ** 2) + ((cos(((pickup_longitude * 3.141592653589793) / 180)) * cos(((dropoff_longitude * 3.141592653589793) / 180))) * (sin(((((dropoff_latitude - pickup_latitude) / 2) * 3.141592653589793) / 180)) ** 2))))))) * 3958.8)',\n",
       "    'arguments': ['pickup_latitude',\n",
       "     'pickup_longitude',\n",
       "     'dropoff_latitude',\n",
       "     'dropoff_longitude'],\n",
       "    'argument_dtypes': ['float32', 'float32', 'float32', 'float32'],\n",
       "    'return_dtype': 'float32',\n",
       "    'verbose': False}},\n",
       "  '_jit_1': {'cls': 'vaex.expression.FunctionSerializableNumba',\n",
       "   'state': {'expression': 'rad2deg(arctan2((dropoff_longitude - pickup_longitude), (dropoff_latitude - pickup_latitude)))',\n",
       "    'arguments': ['dropoff_longitude',\n",
       "     'pickup_longitude',\n",
       "     'dropoff_latitude',\n",
       "     'pickup_latitude'],\n",
       "    'argument_dtypes': ['float32', 'float32', 'float32', 'float32'],\n",
       "    'return_dtype': 'float32',\n",
       "    'verbose': False}},\n",
       "  'incremental_prediction_function': {'cls': 'vaex.ml.sklearn.IncrementalPredictor',\n",
       "   'state': {'batch_size': 11000000,\n",
       "    'features': ['PCA_0',\n",
       "     'PCA_1',\n",
       "     'PCA_2',\n",
       "     'PCA_3',\n",
       "     'standard_scaled_arc_distance',\n",
       "     'pickup_time_x',\n",
       "     'pickup_day_x',\n",
       "     'direction_angle_x',\n",
       "     'pickup_time_y',\n",
       "     'pickup_day_y',\n",
       "     'direction_angle_y',\n",
       "     'pickup_is_weekend'],\n",
       "    'model': 'gANjc2tsZWFybi5saW5lYXJfbW9kZWwuX3N0b2NoYXN0aWNfZ3JhZGllbnQKU0dEUmVncmVzc29y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\\nAAAwLjIzLjFxNXViLg==\\n',\n",
       "    'num_epochs': 1,\n",
       "    'partial_fit_kwargs': {},\n",
       "    'prediction_name': 'predicted_duration_min',\n",
       "    'shuffle': False,\n",
       "    'target': 'trip_duration_min'}}},\n",
       " 'selections': {'__filter__': {'type': 'expression',\n",
       "   'boolean_expression': '((((((((__pickup_longitude > -74.05) & (__pickup_longitude < -73.75)) & (__pickup_latitude > 40.58)) & (__pickup_latitude < 40.9)) & (__dropoff_longitude > -74.05)) & (__dropoff_longitude < -73.75)) & (__dropoff_latitude > 40.58)) & (__dropoff_latitude < 40.9))',\n",
       "   'mode': 'and',\n",
       "   'previous_selection': {'type': 'expression',\n",
       "    'boolean_expression': '((trip_speed_mph > 1) & (trip_speed_mph < 60))',\n",
       "    'mode': 'and',\n",
       "    'previous_selection': {'type': 'expression',\n",
       "     'boolean_expression': '((trip_duration_min > 3) & (trip_duration_min < 25))',\n",
       "     'mode': 'and',\n",
       "     'previous_selection': {'type': 'expression',\n",
       "      'boolean_expression': '((trip_distance > 0) & (trip_distance < 7))',\n",
       "      'mode': 'and',\n",
       "      'previous_selection': {'type': 'expression',\n",
       "       'boolean_expression': '((passenger_count > 0) & (passenger_count < 7))',\n",
       "       'mode': 'and',\n",
       "       'previous_selection': None}}}}}},\n",
       " 'ucds': {},\n",
       " 'units': {},\n",
       " 'descriptions': {},\n",
       " 'description': 'file exported by vaex, by user jovan, on date 2020-06-03 17:04:18.044915, from source /has/no/path/arraysprevious description:\\nfile exported by vaex, by user jovan, on date 2019-05-02 19:16:24.798101, from source /Users/jovan/Work/vaex-dev/vaex-demo-taxi/data/yellow_taxi_2009_2015.hdf5previous description:\\nfile exported by vaex, by user jovan, on date 2019-04-13 02:31:19.400663, from source /Volumes/Elements-U/Jovan/vaex-datasets/nyc_taxi/yellow_taxi_2009.hdf5-/Volumes/Elements-U/Jovan/vaex-datasets/nyc_taxi/yellow_taxi_2010.hdf5-/Volumes/Elements-U/Jovan/vaex-datasets/nyc_taxi/yellow_taxi_2011.hdf5-/Volumes/Elements-U/Jovan/vaex-datasets/nyc_taxi/yellow_taxi_2012.hdf5-/Volumes/Elements-U/Jovan/vaex-datasets/nyc_taxi/yellow_taxi_2013.hdf5-/Volumes/Elements-U/Jovan/vaex-datasets/nyc_taxi/yellow_taxi_2014.hdf5-/Volumes/Elements-U/Jovan/vaex-datasets/nyc_taxi/yellow_taxi_2015.hdf5',\n",
       " 'active_range': [0, 151762675],\n",
       " 'column_aliases': {}}"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_train.state_get()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Write the state to disk (serializes the operations and model)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-06-10T17:22:01.713810Z",
     "start_time": "2020-06-10T17:22:01.709900Z"
    }
   },
   "outputs": [],
   "source": [
    "df_train.state_write('./taxi_ml_state.json')"
   ]
  }
 ],
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